In the increasingly mobile modern economy, it becomes more and more important for users to be capable of performing various activities traditionally requiring physical documents via mobile devices. For example, processing payments memorialized on financial documents, and authenticating one's identity using an ID.
Accordingly, digital images of a document such as a letter, a check, a bill, an invoice, etc., may be captured using the camera of a mobile device, and processed on-device or uploaded to a backend server for processing. Many such image capture and processing algorithms have been developed, but conventional image capture and processing algorithms fail to reliably detect document edges within the image, especially when the document background and/or image background are similar in texture, color, etc. and/or complex, such as is common for many check backgrounds depicting e.g. a scenic photograph, or IDs depicting a complex hologram, seal, photograph, etc.
In addition, even where document edges may be detected properly, it is a particular challenge to ensure an image of the document is properly oriented for subsequent processing. Since many documents are rectangular in shape, the position of the document edges cannot be consistently relied upon to distinguish alternative vertical orientations, particularly upside down from right-side up. Accordingly, document geometry is not suitable for reliable orientation of a document exhibiting a particular skew angle in a captured image.
In view of the foregoing problems with conventional approaches to mobile image capture and processing, it would be advantageous to provide techniques that improve upon the conventional approach both with respect to accuracy and fidelity of document edge detection and document orientation. Even more advantageous would be improved techniques that simultaneously improve the performance of the mobile device as an image processing platform by reducing computational cost associated with achieving high quality processed images.